Your browser will no longer run
simulation models on

because it lacks support of the Java plug-in required to run Java applets.
Learn more at the official Java website.

Please use one of the following browsers that support Java technology:



Social network - Social Dynamics

Social network

The model illustrates information spreading process in a simple social network. The model is formed by a fixed number of users, messaging each other. Each user has some individual parameters (name, age, city of residence, etc.) and a list of friends with whom user interacts.
The initial size of friend list depends on user's activity (parameter, which is assigned a random value from 0 to 100%). The higher the value, the more friends user has. Friendship probability is higher, the smaller the difference between users age is. In addition, probability of friendship between users from different cities is lower.

The model has two main types of dynamics. First, user's friend list changes over time. At random time intervals, distributed exponentially, users delete the least active friend from their friend list and add a new one instead.
Second, each user posts new messages with a given rate (which depends on user's activity). There are three equiprobable types of messages: messages posted by user on his page, messages posted by user on friend's page and reposts (messages being copied from the friend's page).

The main purpose of this model is evaluation of information spreading process properties in a simple social network. After the button is clicked, random user becomes a source of new information message, which he posts at his page, so it becomes available for reposting. Also, users that learned the new information may post it to their friend's page. The collected statistics describes the dynamics of this process.

The model provides two ways to visualize user's activities:
- standard user's personal page view;
- simplified social graph view, which shows the information spreading process and allows to analyze the communications between users.

Related Models